Analysing Intersectionality (Paperback)

Keming Yang

ISBN 10: 1529789877 / ISBN 13: 9781529789874

Published by SAGE Publications Ltd, London, 2023

About this Item

Paperback. How can we analyse the intersectional effects of multiple factors on experiences of disenfranchisement? This book equips you with the methodological tools to uncover new insights.First providing a critical examination of long-standing methodologies in intersectionality research, it then shines a spotlight on analytical techniques such as qualitative comparative analysis, multilevel models, mediation and moderation, and mixed methods designs.With chapter objectives, real-world research examples, further reading and reflective questions, it will equip you with the methodological tools to understand intersectionality in specific social settings.The book:* Bridges the gap between intersectionality as a theory and an empirical research practice.* Extends existing approaches to analysing intersectionality in a traditionally qualitative field.* Inspires creativity and celebrates a variety of effective methods for studying intersectionality.Innovative and thought-provoking, this book is ideal for any student or researcher looking to harness the power of empirical evidence to explore inequality and injustice. Innovative and practical, this is the perfect methods book for anyone looking to apply intersectionality to their research and their multifaceted data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781529789874

Bibliographic Details

• Title: Analysing Intersectionality (Paperback)
• Publisher: SAGE Publications Ltd, London
• Publication Date: 2023
• Language: English
• ISBN 10: 1529789877
• ISBN 13: 9781529789874
• Binding: Paperback
• Condition: new

About this title

Synopsis

How can we analyse the intersectional effects of multiple factors on experiences of disenfranchisement? This book equips you with the methodological tools to uncover new insights.

First providing a critical examination of long-standing methodologies in intersectionality research, it then shines a spotlight on analytical techniques such as qualitative comparative analysis, multilevel models, mediation and moderation, and mixed methods designs.

With chapter objectives, real-world research examples, further reading and reflective questions, it will equip you with the methodological tools to understand intersectionality in specific social settings.

The book:

·       Bridges the gap between intersectionality as a theory and an empirical research practice.

·       Extends existing approaches to analysing intersectionality in a traditionally qualitative field.

·       Inspires creativity and celebrates a variety of effective methods for studying intersectionality.

Innovative and thought-provoking, this book is ideal for any student or researcher looking to harness the power of empirical evidence to explore inequality and injustice.

About the Author

Dr Keming Yang is currently an Associate Professor of Sociology at University of Durham in the UK. He was born and grew up in the city of Tianjin, People’s Republic of China. He studied sociology at Nankai University and worked there for three years before going to study for a PhD at Columbia University in the US. His first job after receiving the PhD was at National University of Singapore. He then took a position at University of Reading in the UK and moved to the current position at Durham. His first research area is the political and economic sociology of entrepreneurship in China, in which he published two books, Entrepreneurship in China and Capitalists in Communist China, and some articles. Since working at University of Durham, he has been working on the issue of loneliness from a sociological perspective. He is the author of Loneliness: A Social Problem and many articles on this topic. He also has research interest in research methods in the social sciences, and he is the author of Making Sense of Statistics in Social Research and the editor of Categorical Data Analysis.